Triple
T9821271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eure-et-Loir |
E238535
|
entity |
| Predicate | regionCapitalDistanceTo |
P79023
|
FINISHED |
| Object | Chartres is about 90 km southwest of Paris |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Chartres is about 90 km southwest of Paris | Statement: [Eure-et-Loir, regionCapitalDistanceTo, Chartres is about 90 km southwest of Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionCapitalDistanceTo Context triple: [Eure-et-Loir, regionCapitalDistanceTo, Chartres is about 90 km southwest of Paris]
-
A.
regionCapitalDistanceRelation
chosen
Indicates a relationship specifying the distance between a region and its capital.
-
B.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
C.
stateCapitalProximity
Indicates the spatial closeness or distance between a state’s capital city and another specified location.
-
D.
prefectureCapitalDistance
Indicates the distance between a prefecture and its designated capital city.
-
E.
hasCountyCapitalDistance
Indicates a distance relationship specifying how far a county is from its capital.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3147ecc81908cfca84c05a367d9 |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:31 p.m.